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Posted by Kathryn Cave on March 13 2014
Posted by Kathryn Cave on March 13 2014
Between Google's January £400 million purchase of DeepMind and IBM's recent competition to find new uses for supercomputer Watson, the media spotlight seems to be gradually honing in on Artificial Intelligence (AI). We speak to professional insiders to find out if 2014 really is the year for AI.
"I have a list of things I expect people to do with Watson, but by unleashing it to people in Brazil and Africa and China, as well as Silicon Valley, who knows what they'll come up with. That's the intrigue behind having a contest," said Jerry Cuomo, IBM fellow and CTO for WebSphere about the IBM Watson Mobile Developer Challenge, which invites software developers to produce apps that make use of Watson's resources.
This certainly opens up a lot of scope for progression in Artificial Intelligence, especially when you consider the increased emphasis on machine learning and robotics from companies like Google, which has been gradually acquiring organisations in this space. In December there was Boston Dynamics, in January there was UK startup DeepMind, and then there were all those smaller deals like DNNresearch along with seven robotics companies at the tail end of 2013.
So where is Artificial Intelligence likely to go in the near term, medium term and long term?
Neil Lawrence, Professor of Machine Learning at the University of Sheffield who works with colleagues on DeepMind and Google says: “The investments we are seeing [by big companies] are very large because there is a shortage of expertise in this area. In the UK we are lucky to have some leading international groups, however the number of true experts in the UK still numbers in the tens rather than the hundreds.”
“The DeepMind purchase reflects this,” he continues. “Their staff was made up in large part by recent PhD graduates from some of these leading groups. Although even in this context the 400 million dollar price tag still seems extraordinary to many in the field. The year 2014 is not the year in which these developments happened, but it may be the year in which they've begun to impinge upon the public consciousness.”
“I think 2014 is the year where we see an increased use in AI,” agrees Lawrence Flynn, CEO of natural language interaction specialists Artificial Solutions. “But it will take time for AI implementations such as Watson and our own Teneo Network of Knowledge to become widely established [and] for AI to become commonplace.”
Dr Ben Medlock, Chief Technology Officer at SwiftKey, a smart text prediction software company clarifies: “I think AI will become increasingly visible in 2014 as the foundation of a new range of applications and products. We're excited about the potential of AI technology to make interaction with devices more personal, engaging and ‘human’. However, investment in such technologies is a long term commitment, and we're still far from reaching our full potential in this area. We should expect progress to continue well into the next decade and beyond.”
“Initially, AI will be mostly used for personalization,” says Flynn. “For instance, if you always choose sushi every time your mobile personal assistant offers you a choice of nearest restaurants, eventually it will stop giving you a choice and just the directions to the sushi bar. If you always fly business class with British Airways, then why bother the user with a choice of flights from other airlines.”
Lawrence is keen to stress “that it is not in industry where the breakthroughs have happened, but in academia.” He adds: “A particular focus of my own group is dealing with 'massive missing data': where most of the information we would like to have to base our decisions on is not available. Beyond my own area of research there are also key challenges in the areas of planning and reasoning. It is not yet clear to me how the recent breakthroughs will affect these areas.”
While Medlock feels in the near future “[there is likely to be] an increased investment in businesses focused on AI, as the industry begins to understand that these technologies will underpin many [future] products.”
Lawrence thinks the long term future for AI “is very bright, but progress will be steady, not with large single steps forward, but across a number of applications.”
Flynn in turn stresses: “I don’t believe there will be one big AI moment that history will point to, it will just gradually start to become a normal part of our everyday lives. As devices, appliances, transportation [and so on] become intrinsically connected to each other and the internet, so AI will develop further to ensure seamless interaction between them all.”
“Expectations may currently be too high for the immediate future,” says Lawrence. “We are still many years away from achieving many of our goals in artificial intelligence research. The current successes have emerged from an area known as machine learning, a foundational technique that already underpinned much of the data driven decision making of the large internet companies.”
“The methodologies used have mainly emerged from a relatively small annual conference known as NIPS,” he adds. “The recent breakthroughs emerged from a group of NIPS researchers who received very far-sighted funding from the Canadian government (the Canadian Institute for Advanced Research NCAP program). The program spent a relatively small amount of money (tens of millions) on a carefully selected group of people. This group was led by Geoff Hinton (now of Google) and advised by Yann LeCun (now of Facebook).”
“In the UK, for example,” he continues, “large amounts of money are now promised, but it is not at all clear whether it will be well spent. Functional research operates rather like a well-tended garden: it needs an understanding of the right sort of plants and the ideal conditions for them. A sudden large increase in funding can have a similar effect to indiscriminate application of manure: something will grow, but it's not clear at the outset what it will be. When it comes to harvest time, will we have roses or dock leaves? The Canadian approach was to select the roses first, and then carefully tend them. Other countries would do well to follow a similar approach if they want to reap similar rewards.”
The view from industry is also similar. Matlock looks at the future in terms of the next couple of decades and in this time frame he believes: “AI research will lead us towards more general solutions, able to take diverse inputs from a wide range of data sources and make powerful predictions that closely mimic higher order human reasoning. We will harness the rich streams of data harvested from personal/wearable devices and feed them into these general purpose AI problem solvers, providing support for important life decisions and enhancing our general health and wellbeing.”
Whilst Flynn says “[although] we are very excited by the possibilities that AI opens up in the next few years, ironically it’s likely that by the time AI is mainstream in every home that consumers won’t even think about it. As far as they are concerned, a product or service works how it’s supposed to and most of the time that’s what people care about.”
The start may be slow but as Flynn concludes: “In the longer term [more than 20 years] I expect AI research to help us explore some of our deepest questions around life, purpose, consciousness and what it means to be human.”
It will be interesting to see whether this comes true within any of our lifetimes.
Kathryn Cave is Editor at IDG Connect